Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Applicant's submission filed on 12/16/2025 has been entered. Claim(s) 1-20 is/are pending in the application.
Claim Rejections - 35 USC § 101
1 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim(s) 1 is/are drawn to method (i.e., a process), claim(s) 11is/are drawn to a system (i.e., a machine/manufacture), and claim(s) 16 is/are drawn to non-transitory computer readable medium (i.e., a machine/manufacture). As such, claims 1, 11, and 16 is/are drawn to one of the statutory categories of invention.
Claims 1-20 are directed to determining a classification. Specifically, the claims recite determining a classification result of the device based on selecting at least one of the first classification or the second classification, selecting the first classification to provide a first property of the device based on a priority algorithm, and selecting the second classification to provide a second property of the device based on the priority algorithm, and determining the classification result as a combination of device properties that comprises the first property and the second property, which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (fundamental economic principles or practices including hedging insurance, mitigating risk) OR (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) OR (managing personal behavior or relationships or interactions between people including social activities teaching, and following rules or instructions) OR Mental Processes and is similar to the concept of (concepts performed in the human mind (including an observation, evaluation, judgement, opinion) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 54-55 (January 7, 2019)), the additional element(s) of the claim(s) such as memory, processing device, computer readable medium merely use(s) a computer as a tool to perform an abstract idea and/or generally link(s) the use of a judicial exception to a particular technological environment. Specifically, the memory, processing device, computer readable medium perform(s) the steps or functions of obtaining a first and second classification. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a memory, processing device, computer readable medium to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of determining a classification. As discussed above, taking the claim elements separately, the memory, processing device, computer readable medium perform(s) the steps or functions of obtaining a first and second classification These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of determining a classification. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
Dependent claims 2-10, 12-15, 17-20 further describe the abstract idea of determining a classification. The dependent claims do not include additional elements that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. Therefore, the dependent claims are also not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-9, 11-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gupta (U.S. Patent 11102093) further in view of Vasudevan (U.S. Patent App Pub 20210204152).
Regarding claim 1,
Gupta teaches a method, comprising: obtaining a first classification of a device on a network from a first source; (See claim 1, figure 4, column 18 line 34 – column 19 line 53, Gupta teaches first device reputation score based on infected with malware)
obtaining a second classification of the device on the network from a second source wherein the first classification and the second classification are different; and (See claim 1, figure 4, column 18 line 34 – column 19 line 53, Gupta teaches second device reputation score based on network activity and they are different)
determining a classification result of the device based on selecting at least one of the first classification or the second classification. (See claim 1, 9, figure 4, column 3 line 60 – column 4 line 7, column 19 lines 11-28, Gupta teaches selecting a reputation score)
Gupta does not explicitly teach but Vasudevan teaches selecting the first classification to provide a first property of the device based on a priority algorithm, and selecting the second classification to provide a second property of the device based on the priority algorithm, and determining the classification result as a combination of device properties that comprises the first property and the second property.(See paragraphs 7-9, 57, figures 1-2, Vasudevan teaches two classifiers for traffic flows then applying priority selector algorithm that choose between them based on confidence scores and historical relevance to determining QOS priority.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have known to combine the teachings of Vasudevan with Gupta because both deal with scoring devices. The advantage of incorporating the above limitation(s) of Vasudevan into Gupta is that Vasudevan teaches a communication device ensure robustness of the system to improve accuracy of classification, and improve the overall ensemble of classifiers, therefore making the overall system more robust and efficient. (See paragraphs [0002] - [0003],[0038], Vasudevan)
** Examiner’s Note: The claim is broad, because the determine step is based on selecting one or the other first or second which may render other limitations contingent and therefore those limitations may not be given patentable weight.
Regarding claim 2
Gupta and Vasudevan teach the method of claim 1, determining the classification result of the device includes referencing the configuration file that includes a first score associated with the first source and a second score associated with the second source. (See claim 1, figure 4, column 18 line 34 – column 19 line 53, Gupta teaches reputation scores)
Further, Vasudevan teaches wherein the priority algorithm comprises a configuration file. (See paragraphs 18-20, Vasudevan) See motivation to combine for claim 1.
Regarding claim 3
Gupta and Vasudevan teach the method of claim 2, wherein the configuration file includes a respective score for each property of a plurality of devices as determined by each of a plurality of sources. (See column 19 lines 10-29, Gupta teaches scoring a plurality of devices)
Regarding claim 4
Gupta and Vasudevan teach the method of claim 2wherein the first source has a higher score with respect to the first property than the second source. (See column 3 line 52 – column 4 line 6, 19 lines 10-29, claim 1, 9, , Gupta teaches scores of the reputations can be higher and lower)
Regarding claim 5
Gupta and Vasudevan teach the method of claim 1, wherein determining the classification result of the device comprises translating at least one of the first classification or the second classification to a standard nomenclature having a predefined set of symbols and ordering . (See column 3 lines 30-67, Gupta teaches thresholds a and sla which translate classes a host may be designated as “Good” if it has a reputation between 0.7 and 1 (assuming a reputation scale of −1 to 1), “OK” if it has a reputation less than 0.7 but greater than 0, and “Bad” if it has a negative reputation. The reputation score can be calculated exclusively from analysis of network traffic or activity in a data center. )
Regarding claim 6
Gupta and Vasudevan teach the method of claim 1, wherein determining the classification result of the device includes selecting one of the first classification or the second classification based on a depth properties of of the first classification and a depth of proeprties of the second classification. (See column 3 lines 30-67, Gupta teaches an sla which is a depth of a class based on contract)
Regarding claim7,
Gupta and Vasudevan teach the method of claim 1, wherein a new classification is obtainable from a new source in response to the new source being added to a source configuration file, wherein the source configuration file identifies a plurality of sources that a respective classification is obtainable from, and identifies each property name that is associated with each of the plurality of sources.(See figure 7b, column 3 lines 45-67, column 22 lines 29-35, Gupta teaches different sources of reputation)
Regarding claim 8
Gupta and Vasudevan teach the method of claim 1, further comprising publishing the classification result and a source of the classification result. See column 3 line 52 – column 4 line 6, 19 lines 10-29, claim 1, Gupta teaches scoring a plurality of devices with different reputation scores and source of the scores )
Regarding claim 9
Gupta and Vasudevan teach the method of claim 1, wherein the first source determines the first classification based on a fingerprint in network traffic.(See column 45-67, Gupta teaches network traffic for one of the scores)
Regarding claim 11,
Gupta teaches a system, comprising: a computer readable memory; and a processing device, operatively coupled to the computer readable memory, to: obtain a first classification of a device on a network from a first source; (See claim 1, figure 4, column 18 line 34 – column 19 line 53, Gupta teaches first device reputation score based on infected with malware)
obtain a second classification of the device on the network from a second source wherein the first classification and the second classification are different; (See claim 1, figure 4, column 18 line 34 – column 19 line 53, Gupta teaches second device reputation score based on network activity and they are different)
determine a classification result of the device based on selecting at least one of the first classification or the second classification; and (See claim 1, 9, figure 4, column 3 line 60 – column 4 line 7, column 19 lines 11-28, Gupta teaches selecting a reputation score)
store the classification result to the computer readable memory.(See column 18 line 59 – column 19 28, col 18 lines 1-10, figures 3-4, Gupta teaches storing the classification result)
Gupta does not explicitly teach but Vasudevan teaches to select the first classification to provide a first property of the device based on a priority algorithm, and select the second classification to provide a second property of the device based on the priority algorithm, and determining the classification result as a combination of device properties that comprises the first property and the second property.(See paragraphs 7-9, 57, figures 1-2, Vasudevan teaches two classifiers for traffic flows then applying priority selector algorithm that choose between them based on confidence scores and historical relevance to determining QOS priority.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have known to combine the teachings of Vasudevan with Gupta because both deal with scoring devices. The advantage of incorporating the above limitation(s) of Vasudevan into Gupta is that Vasudevan teaches a communication device ensure robustness of the system to improve accuracy of classification, and improve the overall ensemble of classifiers, therefore making the overall system more robust and efficient. (See paragraphs [0002] - [0003], [0038], Vasudevan)
Claims 12-15 list all the same elements of claims 2-5, but in system form rather than method form. Therefore, the supporting rationale of the rejection to claims 2-5 applies equally as well to claims 12-15.
Claims 16-20 list all the same elements of claims 1, 6-9, but in medium form rather than method form. Therefore, the supporting rationale of the rejection to claims 1, 6-9 applies equally as well to claims 16-20. Furthermore with regards to the limitation of 16. A non-transitory computer readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to: (See column 22 lines 20-31, Gupta)
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gupta (U.S. Patent 11102093) in view of Vasudevan (U.S. Patent App Pub 20210204152). in view of Zimmer (U.S. Patent App Pub 20180096260)
Regarding claim 10,
Gupta and Vasudevan teach the method of claim 9. Gupta does not explicitly teach but Zimmer teaches the wherein the second source determines the second classification based on applying a machine learning algorithm to network traffic. (See paragraphs 47-48, 63, claim 5, figures 4a and 4b, Zimmer teaches machine learning for scores)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have known to combine the teachings of Zimmer with Gupta and Vasudevan because both deal with scoring devices. The advantage of incorporating the above limitation(s) of Zimmer into Gupta and Vasudevan is that Zimmer enables receiving feedback from remote administrator, information technology Administrators, and device users through an interface to reduce false positives and fine tune learning algorithm so as to improve learning by cloud-based machine learning module by providing feedback and corrections to past inference errors and mischaracterizations, therefore making the overall system more robust and efficient. (See paragraphs [0004] - [0006], Zimmer)
Response to Arguments
4. Applicant's arguments filed 12/16/2025 have been fully considered but they are not persuasive.
A. Applicant argues that the claims are not directed to a judicial exception under Step 2A Prong One. As for Step 2A Prong One, of the Abstract idea is directed towards the abstract idea of determining a classification result which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (fundamental economic principles or practices including hedging insurance, mitigating risk) OR (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) OR (managing personal behavior or relationships or interactions between people including social activities teaching, and following rules or instructions) OR Mental Processes and is similar to the concept of (concepts performed in the human mind (including an observation, evaluation, judgement, opinion) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
B. Applicant argues that the claims are not directed to a judicial exception under Step 2A Prong Two. As for Step 2A Prong Two, the claim limitations do not include additional elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, and the claim is not more than a drafting effort designed to monopolize the judicial exception and the claim limitation simply describe the abstract idea. The limitation directed to determining a classification result does not add technical improvement to the abstract idea. The recitations to “a computer readable memory; and a processing device, operatively coupled to the computer readable memory, and a nontransitory computer readable medium” perform(s) the steps or functions of obtaining a first classification of a device on a network from a first source;obtaining a second classification of the device on the network from a second source wherein the first classification and the second classification are different. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
C. Applicant argues that the claims are not directed to a judicial exception under Step 2B.
As for Step 2B, The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the limitation directed to determining a classification result does not add significantly more to the abstract idea. Furthermore, using well-known computer functions to execute an abstract idea does not constitute significantly more. The recitations to a computer readable memory; and a processing device, operatively coupled to the computer readable memory, and a nontransitory computer readable medium” are generically recited computer structure. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of determining a classification result. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible. Further the priority algorithm is simple selector and part of the abstract idea. Since it is part of the abstract idea is not used to transform the abstract idea into a
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and located in the PTO-892 form.
1.Christodorescu, U.S. Patent App 20180198812, teaches various embodiments provide methods, devices, and non-transitory processor-readable storage media for detecting anomalies in network traffic patterns with a network device by analyzing patterns in network traffic packets traversing the network. Various embodiments include clustering received network traffic packets into groups. The network device receives data packets originating from an endpoint device and analyzes the packets for patterns. The network device may apply a traffic analysis model to the clusters to obtain context classes. The network device may select a behavior classifier model based, at least in part, on the determined context class, and may apply the selected behavior classifier model to determine whether the packet behavior is benign or non-benign.
2. Haefner, U.S. Patent 11115289, teaches a security apparatus has a memory device and a processor that is in connected with the memory device. The processor determines a complexity score for the first electronic device. A behavioral pattern is established for the first electronic device operating within the local network. A confidence metric for the first electronic device is calculated based on the determined complexity score and the established behavioral pattern. The access of the first electronic device is controlled to the external electronic network according to the calculated confidence metric.
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/NINOS DONABED/Primary Examiner, Art Unit 2444